C&EN

Automated Machine-Learning-Driven Analysis of Microplastics by TGA-FTIR for Enhanced Identification and Quantification

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Microplastics persist as ubiquitous environmental contaminants, and efficient methods ...
Scientific Research Publishing

Suykens, J.A.K. and Vandewalle, J. (1999) Least Squares Support Vector Machine Classifiers. Neural Processing Letters, 9, 293-300.

ABSTRACT: Rail corrugation, as a prevalent type of rail damage in heavy railways, induces diseases in the track structure. In order to ensure the safe operation of trains, an improved whale ...
IEEE

Design and Implementation of a Light-Weight Channel Vector Classifier Based on Support Vector Machine for Real-Time 5G Beam Index Detection

Abstract: Machine Learning (ML) is recently considered a key technology for bringing outstanding performance to wireless communications. Conventional research has highlighted the potential of Support ...
GitHub

Support Vector Machine Classifier from scratch

An implementation of a support vector machine classifier written in python for multiclass classification problems. Internally the cvxopt package is used to solve the quadratic programming optimization ...
IEEE

Unit Commitment Predictor With a Performance Guarantee: A Support Vector Machine Classifier

Abstract: The system operators usually need to solve large-scale unit commitment problems within limited time frame for computation. This paper provides a pragmatic solution, showing how by learning ...
Scientific Research Publishing

Suykens, J. and Vandewalle, J. (1999) Least Squares Support Vector Machine Classifiers. Neural Processing Letters, 9, 293-300.

ABSTRACT: In this paper, we modify the Bregman APGs (BAPGs) method proposed in (Wang, L, et al.) for solving the support vector machine problem with truncated loss (HTPSVM) given in (Zhu, W, et al.), ...
marktechpost

Researchers from Tsinghua University Proposes a Novel Slide Loss Function to Enhance SVM Classification for Robust Machine Learning

In machine learning, one method that has consistently demonstrated its worth across various applications is the Support Vector Machine (SVM). Known for its adeptness at parsing through ...
ascopubs.org

Three Immunomarker Support Vector Machines–Based Prognostic Classifiers for Stage IB Non–Small-Cell Lung Cancer

Phase I Study of Lapatinib in Combination With Chemoradiation in Patients With Locally Advanced Squamous Cell Carcinoma of the Head and Neck We used computer-generated random numbers to study 148 ...